Cognitive radio systems in LTE networks

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The most important fact in the mobile industry at the moment is that demand for wireless services will continue to expand in the coming years. Therefore, it is vital to find more spectrums through cognitive radios for the growing numbers of services and users. However, the spectrum reallocations, enhanced receivers, shared use, or secondary markets-will not likely, by themselves or in combination, meet the real exponential increases in demand for wireless resources. Network operators will also need to re-examine network architecture, and consider integrating the fibre and wireless networks to address this issue. This thesis involves driving fibre deeper into cognitive networks, deploying microcells connected through fibre infrastructure to the backbone LTE networks, and developing the algorithms for diverting calls between the wireless and fibre systems, introducing new coexistence models, and mobility management. This research addresses the network deployment scenarios to a microcell-aided cognitive network, specifically slicing the spectrum spatially and providing reliable coverage at either tier. The goal of this research is to propose new method of decentralized-to-distributed management techniques that overcomes the spectrum unavailability barrier overhead in ongoing and future deployments of multi-tiered cognitive network architectures. Such adjustments will propose new opportunities in cognitive radio-to-fibre systematic investment strategies. Specific contributions include: 1) Identifying the radio access technologies and radio over fibre solution for cognitive network infrastructure to increase the uplink capacity analysis in two-tier networks. 2) Coexistence of macro and microcells are studied to propose a roadmap for optimising the deployment of cognitive microcells inside LTE macrocells in the case of considering radio over fibre access systems. 3) New method for roaming mobiles moving between microcells and macrocell coverage areas is proposed for managing spectrum handover, operator database, authentication and accounting by introducing the channel assigning agent entity. The ultimate goal is to reduce unnecessary channel adaptation

Power interchange analysis for reliable vehicle-to-grid connectivity

Due to the progressively growing energy demand, electricl vehicles (EVs) are increasingly replacing unfashionable vehicles equipped with internal combustion engines. The new era of modern grid is aiming to unlock the possibility of resource coordination between EVs and power grid. The goal of including vehicle-to-grid (V2G) technology is to enable shared access to power resources. To define the initiative, this article investigates the bidirectional power flow between EVs and the main grid. The article provides a new algorithm framework for energy optimization that enables real-time decision making to facilitate charge/discharge processes in grid connected mode. Accordingly, the energy flow optimization, communications for data exchange, and local controller are joined to support system reliability for both power grid and EV owners at parking lot sites. The local controller is the key component that collects the EV data for decision making through real-time communications with EV platforms. The main responsibility of this controller is managing the energy flow during the process of real-time charging without impacting the basic functionalities of both grid and EV systems. Finally, a case study of a modified IEEE 13-node test feeder is proposed to validate the impact of energy flow optimization using V2G technology. This visionary concept provides improvement in grid scalability and reliability to grid operations through accessing EV power storage as a complementary resource of future energy systems

Energy efficiency using cloud management of LTE networks employing fronthaul and virtualized baseband processing pool

The cloud radio access network (C-RAN) emerges as one of the future solutions to handle the ever-growing data traffic, which is beyond the physical resources of current mobile networks. The C-RAN decouples the traffic management operations from the radio access technologies, leading to a new combination of a virtualized network core and a fronthaul architecture. This new resource coordination provides the necessary network control to manage dense Long-Term Evolution (LTE) networks overlaid with femtocells. However, the energy expenditure poses a major challenge for a typical C-RAN that consists of extended virtualized processing units and dense fronthaul data interfaces. In response to the power efficiency requirements and dynamic changes in traffic, this paper proposes C-RAN solutions and algorithms that compute the optimal backup topology and network mapping solution while denying interfacing requests from low-flow or inactive femtocells. A graph-coloring scheme is developed to label new formulated fronthaul clusters of femtocells using power as the performance metric. Additional power savings are obtained through efficient allocations of the virtualized baseband units (BBUs) subject to the arrival rate of active fronthaul interfacing requests. Moreover, the proposed solutions are used to reduce power consumption for virtualized LTE networks operating in the Wi-Fi spectrum band. The virtualized network core use the traffic load variations to determine those femtocells who are unable to transmit to switch them off for additional power savings. The simulation results demonstrate an efficient performance of the given solutions in large-scale network models

A framework of network connectivity management in multi-clouds infrastructure

The network function virtualization (NFV) transformation is gaining an incredible momentum from mobile operators as one of the significant solutions to improve the resource allocation and system scalability in fifth-generation (5G) networks. However, the ultra-dense deployments in 5G create high volumes of traffic that pushes the physical and virtual resources of cloud-based networks to edge limits. Consider a distributed cloud, replacing the core network with virtual entities in the form of virtual network functions (VNFs) still requires efficient integration with various underlying hardware technologies. Therefore, orchestrating the distribution of load between cloud geo-datacenters starts by instantiating a virtual and physical network typologies that connect involved front haul with relevant VNFs. In this article, we provide a framework to manage calls within 5G network clusters for efficient utilization of computational resources and also to prevent unnecessary signaling. We also propose a new scheme to instantiate virtual tunnels for call forwarding between network clusters leading to new logic networks that combine geo-datacenters and fronthaul. To facilitate service chaining in cloud, we propose a new enhanced management and orchestration (E-MANO) architecture that brings network traffic policies from the application layer tothe fronthaul for instant monitoring of available resources. We provide analysis and testbed results in support of our proposals. the fronthaul for instant monitoring of available resources. We provide analysis and testbed results in support of our proposals

Adaptive management of cognitive radio networks employing femtocells

Network planning and management are challenging issues in a two-tier network. Tailoring to cognitive radio networks (CRNs), network operations and transmissions become more challenging due to the dynamic spectrum availability. This paper proposes an adaptive network management system that provides switching between different CRN management structures in response to the spectrum availability and changes in the service time required for the radio access. The considered network management system includes conventional macrocell-only structure, and centralized/distributed structures overlaid with femtocells. Furthermore, analytical expressions of per-tier successful connection probability and throughput are provided to characterize the network performance for different network managements. Spectrum access in dynamic radio environments is formulated according to the quality of service (QoS) constraint that is related to the connection probability and outage probability. Results show that the proposed intelligent network management system improves the maximum capacity and reduces the number of blocked connections by adapting between various network managements in response to free spectrum transmission slots. A road map for the deployment and management of cognitive macro/femto networks is also presented

Enabling digital grid for industrial revolution: self-healing cyber resilient platform

The key market objectives driving digital grid development are to provide sustainable, reliable and secure network systems that can support variety of applications against any potential cyber attacks. Therefore, there is an urgent demand to accelerate the development of intelligent Software-Defined Networking (SDN) platform that can address the tremendous challenges of data protection for digital resiliency. Modern grid technology tends to adopt distributed SDN controllers for further slicing power grid domain and protect the boundaries of electric data at network edges. To accommodate these issues, this article proposes an intelligent secure SDN controller for supporting digital grid resiliency, considering management coordination capability, to enable self-healing features and recovery of network traffic forwarding during service interruptions. A set of advanced features are employed in grid controllers to configure the network elements in response to possible disasters or link failures. In addition, various SDN topology scenarios are introduced for efficient coordination and configurations of network domains. Finally, to justify the potential advantages of intelligent secure SDN system, a case study is presented to evaluate the requirements of secure digital modern grid networks and pave the path towards the next phase of industry revolution

6G networks : is this an evolution or a revolution?

The lessons learned from the third industrial revolution taught us that the transformation from mechanical and analog technology to digital electronics have changed the world once and forever. While computers and communication networks have become the new oil that defines the wealth of countries, research and industrial communities have been the driving forces that have made this transition possible. In the future, the same communities and stakeholders are required to enable the transition to net-zero communication networks. With reference to mobile communications, 5G is an evolution from all previous networks with the adoption of new radio access technologies, multisliced architecture, cloud-native and automation, and so on. By definition, 5G is a network that adapts to user needs and dynamic changes in traffic, designed to serve a new class of users: “machines.” Therefore, latency has become a critical metric in 5G. Looking forward, 6G shall employ cell-less access networks, integrated nonterrestrial networks, joint sensing and communications, new spectrums such as terahertz (THz) communications, switching from traditional channel-based design paradigms to designing channels through novel technologies such as intelligent reconfigurable surfaces, open interfaces that interconnect all network functions, end-to-end orchestrators, and, most noticeably, artificial intelligence (AI) machines that govern all functional modules and operational services. The various network functions generate traces of various operations that are ingested into databases; then AI will leverage this data for optimized decisions that are reflected into network status transitions, resource utilization, service enhancement, and ultimately lead to self-synthesizing networks. Built upon commercial clouds, 6G will have the flexibility to scale and restructure for more resilient response to traffic fluctuations and user requirements. To this end, cybersecurity features will become an embedded part of network functions to shield the network services not only from external threats but also from hosting domains. From an air interface perspective, 6G will integrate nonterrestrial (space, air, drone, and ocean) communications technologies to connect and route new users such as drones and coastal trading vessels. Furthermore, future wireless networks need to make use of a spectrum that extends into the optical spectrum and includes the THz range. The channel becomes a critical component due to the impact of blockages and random orientations at these frequencies. Active and passive intelligent reflecting surfaces (IRSs) will become a new wireless system element that will help overcome new challenges related to coverage and the propagation channel

On the Load Balancing of Edge Computing Resources for On-Line Video Delivery

Online video broadcasting platforms are distributed, complex, cloud oriented, scalable, micro-service-based systems that are intended to provide over-the-top and live content to audience in scattered geographic locations. Due to the nature of cloud VM hosting costs, the subscribers are usually served under limited resources in order to minimize delivery budget. However, operations including transcoding require high-computational capacity and any disturbance in supplying requested demand might result in quality of experience (QoE) deterioration. For any online delivery deployment, understanding user's QoE plays a crucial role for rebalancing cloud resources. In this paper, a methodology for estimating QoE is provided for a scalable cloud-based online video platform. The model will provide an adeptness guideline regarding limited cloud resources and relate computational capacity, memory, transcoding and throughput capability, and finally latency competence of the cloud service to QoE. Scalability and efficiency of the system are optimized through reckoning sufficient number of VMs and containers to satisfy the user requests even on peak demand durations with minimum number of VMs. Both horizontal and vertical scaling strategies (including VM migration) are modeled to cover up availability and reliability of intermediate and edge content delivery network cache nodes

Guest editorial: Special issue on enabling massive iot with 6g: Applications, architectures, challenges, and research directions

[No abstract available